Smart RAN investments

With rapidly increasing data consumption the capacity of the RAN is challenged.
While the issue has been postponed in many markets by a recent massive rollout of LTE, the cost of capacity will continue to increase.
Added to this, continued coverage rollout, either basic or increased service, continues to be on the agenda.
The trajectory is clearly not long-term sustainable.
The issues can be further postponed by deploying capacity more focused than the traditional upgrades of the macro network capacity
with uniform upgrades of 3-sector sites and looking at differentiated service levels.
Addressing the situation requires two things: detailed understanding of the impact of the increased capacity on the network and
its financials and a very granular, customer focused approach to investments.

A brief outline of a proposed approach can be found on this page or you can look at my white paper

Process

The basic principle of the proposed approach is as follows:

The idea is to start with articulating the demand side and supply side status and desired or expected evolution,
simulate the impact, understand the cost implications and iterate. Very briefly, the steps are:

Use cases per area contains articulation of what service customers in different areas shall be supplied with in busy hour, e.g. music streaming.

Assumptions on development of usage is the evolution of customer traffic consumption.

Current network status is data on what the network looks like in terms of current sites, usage etc.

Network evolution options reflect what options are defined for the network to meet the basic use cases and the increase in usage.

Simulate impact is used for estimating the impact of the demand and supply side assumptions.
The simulation can be of very different sophistication, depending on the depth of understanding desired and level of effort available.

Cost implications builds an understanding of the impact of the assumptions modelled, integrated with the financial baseline.

Feedback loop reflect that iterations may be required in order to stay within the financial targets.

The more detailed process is outlined below:

The main phases are:

Mobilize: define scope and methodology of process.

Stage setting: set the assumptions on which the strategy is to be built.
This includes the financial assumptions, essentially the limits within the RAN strategy must be built, technology evolution defining the option space from the technology perspective,
current status with a detail defined by the modelling approach, assumptions on the competitors and obtaining best practices as input to the process.

Target customer experience

One of the key areas to define is the target customer experience. Traditional
rollout targets are articulated in engineering terms, either directly through a number of sites or indirectly through a target planning signal level.
Such targets tend to be based on high-level translation of “expected” customer behaviour, but does not consider the actual usage pattern and the number of users.

A more sophisticated approach is to define use cases, e.g. the “killing time with smartphone browsing”, “YouTube video”, “large screen mail synchronisation”.
Through systematic testing, each user story can be associated with a target download speed, latency and idle time.

Assigning use cases and maximum number of users to specific areas will define a required service level.
For example, “peak of 50 killing time with smartphone browsing, 20 with YouTube video and 2 with large screen mail synchronisation” could be a target for a metro station.

This way the service level for the entire territory can be defined.

A key element of the process is the modelling required in the “scenarios and implications” step.
This is key to understanding the impact and is likely to be executed in iterations back and forth with the scenario formulations (and even assumptions).

The general simulation process looks as follows:

The core step, “scenario and capacity simulations” can be of varying sophistication – ranging from network wide modelling in excel to
detailed cell-level simulations with export to a radio planning tool. Various options are discussed in the white paper, with focus on excel based models and a simulation tool based model. The right choice depends upon the desired level of accuracy and the available effort.

For illustration, the picture below shows sites deployed as a result of capacity upgrade requirements in one simulated scenario for a sample network:

The picture shows the capacity builds in a specific year for a sample network. The simulation can include things like which specific sites additional
capacity may be built for, how traffic moves between layers, what the resulting coverage of the capacity rollout is (and therefore what the additional
investments to achieve a specific coverage is), results of priority of use of alternative technologies etc.

Irrespective of modelling approach it is imperative that alignment is ensured between the actual capacity upgrade
criteria and the way the model predicts upgrade needs. The need for this is, of course, obvious, but ensuring it is not trivial since the upgrade
criteria typically is linked to a number of technical parameters in the base station.

Experience and offerings

Having worked extensively with managing the evolution mobile networks, including detailed modelling of implementation scenarios, I can assist in both process and content for driving smart RAN investments.

Experience and offerings

Activity

Contribution

RAN strategy review

Review current direction, practices, network and spectrum utilisation for improvements.

Modelling RAN development

Model scenarios for development of RAN using a specialised cell-level simulation tool or high-level modelling approach. Scenarios can vary a number of parameters, e.g.: